Outbound Load Planning Optimization uses AI to compute the optimal grouping of outbound orders into loads and the assignment of loads to transport vehicles to minimise freight cost and empty miles, enabling higher truck utilisation without service level compromise, by solving a vehicle-loading and route assignment problem under capacity, time-window, and compliance constraints, across outbound logistics and TMS workflows.
Transport planners group orders into loads manually using experience and spreadsheets, typically achieving sub-optimal truck fill rates and inefficient grouping of drop points on the same route. Freight costs per delivery are higher than necessary, and partial loads depart daily due to time pressure rather than fill optimisation.
The AI takes confirmed outbound orders with weight, volume, destination, and delivery time windows, and solves for the load-to-vehicle assignment that maximises load fill and minimises total freight cost across the carrier portfolio. The plan is reviewed by the transport planner before booking confirmation.
Average truck fill rate increases; freight cost per delivery unit decreases.
No intrinsic risk triggered.
No controls triggered.
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